Stardust: tracking activity in a distributed storage system

Performance monitoring in most distributed systems provides minimal guidance for tuning, problem diagnosis, and decision making. Stardust is a monitoring infrastructure that replaces traditional performance counters with end-to-end traces of requests and allows for efficient querying of performance metrics. Such traces better inform key administrative performance challenges by enabling, for example, extraction of per-workload, per-resource demand information and per-workload latency graphs. This paper reports on our experience building and using end-to-end tracing as an on-line monitoring tool in a distributed storage system. Using diverse system workloads and scenarios, we show that such fine-grained tracing can be made efficient (less than 6% overhead) and is useful for on- and off-line analysis of system behavior. These experiences make a case for having other systems incorporate such an instrumentation framework. Categories and Subject Descriptors C.4 [Performance of Systems]: ...

• Type: Conference
• Year: 2006
• Where: SIGMETRICS
• Authors: Eno Thereska, Brandon Salmon, John D. Strunk, Matthew Wachs, Michael Abd-El-Malek, Julio Lopez, Gregory R. Ganger
• Keywords: End-to-end Tracing, Performance, SIGMETRICS 2006, Traditional Performance Counters